code: def warmup(tokenizer, ls_model, hf_model, sentences):
      inputs = tokenizer(sentences, return_tensors="pt", padding=True)
      inputs_id = inputs["input_ids"]
  
      # ls_generate(ls_model, tokenizer, inputs_id)
      hf_generate(hf_model, tokenizer, inputs_id)
  
file_path: lightseq/examples/inference/python/test/ls_bart_bench.py
imports: import time
  import argparse
  import torch
  import lightseq.inference
  from transformers import FSMTForConditionalGeneration, FSMTTokenizer
label_desc: Use image node_id 5 for calling a global function with example usage: warmup(tokenizer, ls_model, hf_model, sentences) without return types